Temporal Correlations of Skin and Blood Metabolites with Clinical Outcomes of Biologic Therapy in Psoriasis

Vending-Machine-Style Skin Excretion Sensing

Skin metabolites show huge potential for use in clinical diagnostics. However, skin sampling and analysis workflows are tedious and time-consuming. Here, we demonstrate a vending-machine-style skin excretion sensing platform based on hydrogel-assisted sampling of skin metabolites. In this sensing platform, a sampling probe with hydrogel is held by a robotic arm. The robotic arm manoeuvres the probe to press it onto the forearm of a human subject. Due to the highly hydrophilic nature of the hydrogel, water-soluble metabolites─released by skin─are collected into the hydrogel, leaving behind the nonpolar metabolites. The probe is then inserted into a custom-made open port sampling interface coupled to an electrospray ion source of a high-resolution quadrupole-time-of-flight mass spectrometer. Metabolites in the hydrogel are immediately extracted by a solvent liquid junction in the interface and analyzed using the mass spectrometer. The ion current of the target analyte is displayed on a customized graphical user interface, which can also be used to control the key components of the analytical platform. The automated sampling and analysis workflow starts after the user inserts coins or presents an insurance card, presses a button, and extends an arm on the sampling area. The platform relies on low-cost mechanical and electronic modules (a robotic arm, a single-board computer, and two microcontroller boards). The limits of detection for standard analytes─arginine, citrulline, and histidine─embedded in agarose gel beds were 148, 205, and 199 nM, respectively. Various low-molecular-weight metabolites from human skin have been identified with the high-resolution mass spectrometer.

Skin Cancer Metabolic Profile Assessed by Different Analytical Platforms

Skin cancer, including malignant melanoma (MM) and keratinocyte carcinoma (KC), historically named non-melanoma skin cancers (NMSC), represents the most common type of cancer among the white skin population. Despite decades of clinical research, the incidence rate of melanoma is increasing globally. Therefore, a better understanding of disease pathogenesis and resistance mechanisms is considered vital to accomplish early diagnosis and satisfactory control. The "Omics" field has recently gained attention, as it can help in identifying and exploring metabolites and metabolic pathways that assist cancer cells in proliferation, which can be further utilized to improve the diagnosis and treatment of skin cancer. Although skin tissues contain diverse metabolic enzymes, it remains challenging to fully characterize these metabolites. Metabolomics is a powerful omics technique that allows us to measure and compare a vast array of metabolites in a biological sample. This technology enables us to study the dermal metabolic effects and get a clear explanation of the pathogenesis of skin diseases. The purpose of this literature review is to illustrate how metabolomics technology can be used to evaluate the metabolic profile of human skin cancer, using a variety of analytical platforms including gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS), and nuclear magnetic resonance (NMR). Data collection has not been based on any analytical method.

Tuning Electrospray Ionization with Low-Frequency Sound

Electrospray ionization (ESI) mass spectrometry (MS) is one of the key techniques used in biomolecular analysis nowadays. It relies on formation of polydisperse microdroplets, which undergo desolvation and liberate ions to the gas phase. Here we demonstrate low-frequency-sound-modulated ESI for analysis of biomolecules. By using a low-frequency (50-350 Hz) sound, it is possible to deflect electrospray microdroplets toward the mass spectrometer's orifice. Microdroplets of different sizes are deflected to a different extent leading to a partial size segregation. This effect leads to either an increase or decrease of MS signal intensity as well as signal-to-noise ratio. It also affects the selectivity of the ESI-MS analysis. The observations are rationalized by taking into account different pathways of ion formation and the likelihood of deflecting microdroplets of certain size. The online ESI-MS observations are supported with offline shadowgraphs obtained at varied sound frequencies, signal amplitudes, and phase shifts.

Metabolomic Analysis and MRM Verification of Coarse and Fine Skin Tissues of Liaoning Cashmere Goat

One of the critical elements in evaluating the quality of cashmere is its fineness, but we still know little about how it is regulated at the metabolic level. In this paper, we use UHPLC–MS/MS detection and analysis technology to compare the difference in metabolites between coarse cashmere (CT_LCG) and fine cashmere (FT_LCG) skin of Liaoning cashmere goats. According to the data, under positive mode four metabolites were significantly up-regulated and seven were significantly down-regulated. In negative mode, seven metabolites were significantly up-regulated and fourteen metabolites were significantly down-regulated. The two groups’ most significant metabolites, Gly–Phe and taurochenodeoxycholate, may be crucial in controlling cashmere’s growth, development, and fineness. In addition, we enriched six KEGG pathways, of which cholesterol metabolism, primary bile acid biosynthesis, and bile secretion were enriched in positive and negative modes. These findings offer a new research idea for further study into the critical elements influencing cashmere’s fineness.

Non-invasive skin sampling detects systemically administered drugs in humans

Clinical testing typically relies on invasive blood draws and biopsies. Alternative methods of sample collection are continually being developed to improve patient experience; swabbing the skin is one of the least invasive sampling methods possible. To show that skin swabs in combination with untargeted mass spectrometry (metabolomics) can be used for non-invasive monitoring of an oral drug, we report the kinetics and metabolism of diphenhydramine in healthy volunteers (n = 10) over the course of 24 hours in blood and three regions of the skin. Diphenhydramine and its metabolites were observed on the skin after peak plasma levels, varying by compound and skin location, and is an illustrative example of how systemically administered molecules can be detected on the skin surface. The observation of diphenhydramine directly from the skin supports the hypothesis that both parent drug and metabolites can be qualitatively measured from a simple non-invasive swab of the skin surface. The mechanism of the drug and metabolites pathway to the skin’s surface remains unknown.

Non-Invasive, Topical Sampling of Potential, Low-Molecular Weight, Skin Cancer Biomarkers: A Study on Healthy Volunteers

Monitoring of low-molecular weight cancer biomarkers, such as tryptophan (Trp) and its derivative kynurenine (Kyn), might be advantageous to non-invasive skin cancer detection. Thus, we assessed several approaches of topical sampling of Trp and Kyn, in relation to phenylalanine (Phe) and tyrosine (Tyr), on the volar forearm of six healthy volunteers. The sampling was performed with three hydrogels (made of agarose or/and chitosan), hydrated starch films, cotton swabs, and tape stripping. The biomarkers were successfully sampled by all approaches, but the amount of collected Kyn was low, 20 ± 10 pmol/cm². Kyn quantification was below LOQ, and thus, it was detected only in 20% of topical samples. To mitigate variability problems of absolute amounts of sampled amino acids, Tyr/Trp, Phe/Trp, and Phe/Tyr ratios were assessed, proving reduced inter-individual variation from 79 to 45% and intra-individual variation from 42 to 21%. Strong positive correlation was found between Phe and Trp, pointing to the Phe/Trp ratio (being in the 1.0-2.0 range, at 95% confidence) being least dependent on sampling materials, approaches, and sweating. This study leads to conclusion that due to the difficulty in quantifying less abundant Kyn, and thus the Trp/Kyn ratio, the Phe/Trp ratio might be a possible, alternative biomarker for detecting skin cancers.

Hydrogels and Cubic Liquid Crystals for Non-Invasive Sampling of Low-Molecular-Weight Biomarkers—An Explorative In Vivo Study

The molecular composition of human skin is altered due to diseases, which can be utilized for non-invasive sampling of biomarkers and disease diagnostics. For this to succeed, it is crucial to identify a sampling formulation with high extraction efficiency and reproducibility. Highly hydrated skin is expected to be optimal for increased diffusion of low-molecular-weight biomarkers, enabling efficient extraction as well as enhanced reproducibility as full hydration represents a well-defined endpoint. Here, the aim was to explore water-based formulations with high water activities, ensuring satisfactory skin hydration, for non-invasive sampling of four analytes that may serve as potential biomarkers, namely tryptophan, tyrosine, phenylalanine, and kynurenine. The included formulations consisted of two hydrogels (chitosan and agarose) and two different liquid crystalline cubic phases based on the polar lipid glycerol monooleate, which were all topically applied for 2 h on 35 healthy subjects in vivo. The skin status of all sampling sites was assessed by electrical impedance spectroscopy and transepidermal water loss, enabling explorative correlations between biophysical properties and analyte abundancies. Taken together, all formulations resulted in the successful and reproducible collection of the investigated biomarkers. Still, the cubic phases had an extraction capacity that was approximately two times higher compared to the hydrogels.

A systematic review: metabolomics-based identification of altered metabolites and pathways in the skin caused by internal and external factors

The skin's ability to function optimally is affected by many diverse factors. Metabolomics has a great potential to improve our understanding of the underlying metabolic changes and the affected pathways. Therefore, the objective of this study was to review the current state of the literature and to perform further metabolic pathway analysis on the obtained data. The aim was to gain an overview of the metabolic changes under altered conditions and to identify common and different patterns as a function of the investigated factors. A cross-study comparison of the extracted studies from different databases identified 364 metabolites, whose concentrations were considerably altered by the following factor groups: irradiation, xenobiotics, aging, and skin diseases (mainly psoriasis). Using metabolic databases and pathway analysis tools the individual metabolites were assigned to the corresponding metabolic pathways and the most strongly affected signaling pathways were identified. All factors induced oxidative stress. Thus, antioxidant defense systems, especially coenzyme Q₁₀  (aging) and the glutathione system (irradiation, aging, xenobiotics) were impacted. Lipid metabolism was also impacted by all factors studied. The carnitine shuttle as part of β-oxidation was activated by all factor groups except aging. Glycolysis, Krebs (TCA) cycle and purine metabolism were mainly affected by irradiation and xenobiotics. The pentose phosphate pathway was activated and Krebs cycle was downregulated in response to oxidative stress. In summary, it can be ascertained that mainly energy metabolism, lipid metabolism, antioxidative defense and DNA repair systems were impacted by the factors studied.

Flat Disc-Shaped Sampling Probe and Online Re-extraction Apparatus for Mass Spectrometric Analysis of Skin Metabolites: A Proof of Concept

Sweat analysis provides an alternative and noninvasive way of clinical diagnostics. However, sampling and transferring sweat-derived samples to analytical instruments is challenging. In this report, we demonstrate a method utilizing a flat disc-shaped sampling probe, and a compatible re-extraction apparatus coupled online with extractive electrospray ionization (EESI) mass spectrometry (MS). The probe enables sampling of metabolites from a skin area of ∼2.2 cm². The subsequent online re-extraction and analysis by EESI-MS further mitigates matrix effects caused by sweat components, thus eliminating sample preparation steps. The total analysis time is only 6 min. We have optimized the key parameters of the system, including flow rate of the nebulizing gas in ESI, pressure of the nebulizing gas in pneumatic sample nebulizer, flow rate of the solvent in ESI, and composition of extractant. The standard solutions (0.1 mL) were supplemented with 0.04 M sodium chloride to mimic the matrix effect normally observed in sweat samples. The method has been characterized with four chemical standards (positive-ion mode of histidine, leucine, urocanic acid; negative-ion mode of lactic acid). The limits of detection range from 1.09 to 95.9 nmol. We have further demonstrated the suitability of the method for analysis of sweat. An attempt was made to identify some of the recorded signals by product-ion scan and accurate/exact mass matching.

Metabolomics Studies in Psoriatic Disease: A Review

Metabolomics investigates a broad range of small molecules, allowing researchers to understand disease-related changes downstream of the genome and proteome in response to external environmental stimuli. It is an emerging technology that holds promise in identifying biomarkers and informing the practice of precision medicine. In this review, we summarize the studies that have examined endogenous metabolites in patients with psoriasis and/or psoriatic arthritis using nuclear magnetic resonance (NMR) or mass spectrometry (MS) and were published through 26 January 2021. A standardized protocol was used for extracting data from full-text articles identified by searching OVID Medline ALL, OVID Embase, OVID Cochrane Central Register of Controlled Trials and BIOSIS Citation Index in Web of Science. Thirty-two studies were identified, investigating various sample matrices and employing a wide variety of methods for each step of the metabolomics workflow. The vast majority of studies identified metabolites, mostly amino acids and lipids that may be associated with psoriasis diagnosis and activity. Further exploration is needed to identify and validate metabolomic biomarkers that can accurately and reliably predict which psoriasis patients will develop psoriatic arthritis, differentiate psoriatic arthritis patients from patients with other inflammatory arthritides and measure psoriatic arthritis activity.

Skin Metabolomics

Skin retains numerous low-molecular-weight compounds (metabolites). Some of these compounds fulfill specific physiological roles, while others are by-products of metabolism. The skin surface can be sampled to detect and quantify skin metabolites related to diseases. Miniature probes have been developed to detect selected high-abundance metabolites secreted with sweat. To characterize a broad spectrum of skin metabolites, specimens are collected with one of several available methods, and the processed specimens are analyzed by chromatography, mass spectrometry (MS), or other techniques. Diseases for which skin-related biomarkers have been found include cystic fibrosis (CF), psoriasis, Parkinson's disease (PD), and lung cancer. To increase the clinical significance of skin metabolomics, it is desirable to verify correlations between metabolite levels in skin and other biological tissues/matrices.